My research is centered around Statistical methods for new technologies used in public health and medical studies. These technologies provide new types of data that are increasing both in size and complexity. I am interested in developing analytic tools that are tailored to specific applications, address the particular subtleties of the problem, and then find the common thread that eventually becomes Statistical methodology. My current scientific research interest centers around sleep research (EEG, polysomnograms), wearable computing (accelerometers, heart monitors), and multimodality brain imaging (SPECT, MRI, CT) with applications to Alzheimer, Multiple Sclerosis, traumatic brain injury, and cancer. My statistical expertise centers around inferential methods for ultra high dimensional data, mixed effects modeling, Bayesian inference, and smoothing.

About Ciprian M. Crainiceanu

My research is centered around Statistical methods for new technologies used in public health and medical studies. These technologies provide new types of data that are increasing both in size and complexity. I am interested in developing analytic tools that are tailored to specific applications, address the particular subtleties of the problem, and then find the common thread that eventually becomes Statistical methodology. My current scientific research interest centers around sleep research (EEG, polysomnograms), wearable computing (accelerometers, heart monitors), and multimodality brain imaging (SPECT, MRI, CT) with applications to Alzheimer, Multiple Sclerosis, traumatic brain injury, and cancer. My statistical expertise centers around inferential methods for ultra high dimensional data, mixed effects modeling, Bayesian inference, and smoothing.

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Johns Hopkins University,
Johns Hopkins Bloomberg School of Public Health

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Bloomberg School of Public Health,
Johns Hopkins Bloomberg School of Public Health